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Through-wall radar (TWR) can image the target of interest and capture the human sensing information. However, the poor human interpretability of TWR images and the lack of effective supervision make the extraction of complete body contour intractable. This letter proposes dual UNet, an unsupervised human contour extraction method for TWR images. Specifically, the method adopts two UNets with the same structure. One serves as the encoder to convert the TWR images into the latent representation. Another serves as the decoder to reconstruct the latent representation into the original images. Reconstruction loss and smooth normalized cut loss are optimized together to offset the dependence on labels and supplement global segment constraints. After training and post-processing, the latent representation can be used as the result of contour extraction. Experimental results show that dual UNet stands out among unsupervised human contour extraction methods in both free space and wall-occlusive scenarios, opening the possibility of learning useful human sensing information from raw TWR images without manual annotations. [ABSTRACT FROM AUTHOR]

In this article, we propose a novel processing algorithm for frequency-modulated continuous-wave (FMCW) ice sounding radar, which addresses the along-track focusing of internal reflecting horizons. It is a modified frequency scaling algorithm that can handle the two-layer medium imaging model as well as the Doppler impact of the motion within the sweep in a nadir-looking radar. The proposed algorithm’s comprehensive derivation and implementation processes are described. In the range-Doppler domain, a really effective formulation for radar signals is also presented, which considers refraction effects and electromagnetic wave propagation velocity changes at the interface of two different media. Point target simulations are carried out to demonstrate the algorithm’s performance. The proposed method is also tested on the real data acquired by the shallow-layer-detection ice sounding radar (SLDISR). The result shows the applicability of the proposed method for imaging the ice sheet. [ABSTRACT FROM AUTHOR]

The spatial correlation of ice-sounding data can be used to trace internal isochronic layers and synchronize the age–depth relationship between different ice core sites, which is difficult using existing imaging methods. In this study, we propose a new algorithm to address the opportunity that applying spatial correlation to ice-sheet imaging offers. The algorithm is a spatial-correlation-based ice-sounding imaging method using fast back projection (FBP) that successfully improves the spatial correlation of imaging results with high efficiency. We give the specific steps to implement the algorithm and apply it to simulate both point targets and ice-sounding radar data to demonstrate its validity in imaging ice sheets. Furthermore, compared with two previous methods, the proposed algorithm improves the spatial correlation without degrading the ability of signal-to-noise ratio (SNR) improvement and processing efficiency. [ABSTRACT FROM AUTHOR]

In this paper, a specially designed guided wave radar device for measuring the liquid level in the nuclear industry is proposed. A split-type design is introduced to adapt to a strong radiation environment. An L-band frequency modulated interrupted continuous wave (FMICW) radar is designed to ensure the signal-to-noise ratio of echo signal after long-distance signal transmission, which provides the isolation between transmitter and receiver of more than 60 dB using the gating technology. To overcome the shortcomings of limited installation and maintenance space, a novel coaxial waveguide probe with a multi-segmental structure is proposed and simulated. An adaptive signal processing algorithm is developed to remove false echoes and eliminate measurement fluctuations. A prototype of the proposed measurement system is fabricated and evaluated. Static and dynamic liquid level experiments are performed in an outdoor environment to assess performance and verify the effectiveness of the proposed radar. The results show that the standard deviation measurement error of the proposed radar is within 0.4 cm. The proposed system is expected to have a high potential for applications in liquid level measurement under complex conditions. [ABSTRACT FROM AUTHOR]

Although the through-the-wall radar imaging (TWRI) system working in the appropriate frequency band can penetrate the nonmetallic obstacles and sense the targets behind, its low imaging spatial resolution hinders the acquisition of more detailed information, such as human pose and shape. This article mainly discusses a deep learning-based human pose and shape recovery method from TWRI images. Inspired by cross-modal learning, the method follows a teacher–student learning pipeline that avoids the heavy cost of manual labeling. Specifically, a camera is attached to the self-develop radar system to simultaneously capture paired red-green-blue (RGB) images and TWRI images in a scenario without wall occlusion. A pose estimation framework (Hourglass) and a semantic segmentation framework (UNet) serve as the teacher network to convert the RGB images into the pose keypoints and the shape masks. By taking inspiration from the topological architecture of these frameworks, a student network radar pose shape network (RPSNet) is designed to extract the information from the corresponding radar images and predict the keypoints and masks that are close to the results above. Instead of learning two single-task objectives independently, multitasking learning is introduced to adaptatively learn common features. When applied to wall-occlusive scenarios, only the radar images are collected and fed into the student network for pose and shape recovery. The advantages of this method over computer vision-based methods for human recovery are demonstrated in scenarios both without and with wall occlusion. [ABSTRACT FROM AUTHOR]

Aeromagnetic noise compensation is a vital part of aerial survey measurement, and its compensation effect directly determines the quality of aeromagnetic survey data. At present, the commonly used compensation model is the T-L model, and the least squares method is used to solve for the coefficients. However, the noise source modeled in the T-L model is incomplete. Since the tail boom cannot be completely rigid, tail-boom swing is an unavoidable problem in aeromagnetic measurement. This kind of swing is the most obvious when the aircraft is maneuvering, and it will significantly interfere with the measurement data of the sensor. In this article, two causes of the swing noise are analyzed, and the nonlinear relationship between the swing displacement and the noise is derived. Since it is difficult to express the nonlinear relationship with mathematical forms to compensate for the aeromagnetic data, we propose a new compensation method that uses a 1-D convolutional neural network to perform secondary compensation on the data already compensated by the T-L model in order to remove the effect of tail-boom swing. The flight experiment data show that the proposed method can significantly improve the quality of aeromagnetic data. Compared with the T-L method, the improve ratio is increased by 60%–100%. It shows that the proposed method has a remarkable compensation effect for aeromagnetic noise. [ABSTRACT FROM AUTHOR]

This letter presents a novel image-based vital sign detection strategy for trapped persons based on the optimized two-dimensional (2-D) ultrawideband (UWB) radar deployment. The main novelty is that the slow-time images based on 2-D radar deployment are created to continuously screen the trapped persons with periodic micromotions in a specific area. According to the optimized deployment, multiple UWB life-detection monostatic radars are distributed and work in a time-division-multiplexing mode. These radars are sequentially controlled and activated to capture information from all possible wave incidents and scattering angles. The 2-D radar deployment is designed and optimized using the multiple-input and multiple-output (MIMO) array topology technique. The vital sign is modeled as the slow-time image, and multiple images might contain the periodic weak responses from the trapped persons. Proof-of-principle experiments were carried out based on an optimized 2-D UWB radar deployment. All observation points in this deployment are sequentially selected to complete the transmission and reception of the UWB monostatic radar. Finally, the experimental results validate the effectiveness of the proposed image-based vital sign strategy on the azimuth locations of the trapped persons. [ABSTRACT FROM AUTHOR]

With phase-sensitive optical time-domain reflectometry (Φ-OTDR), an optic fiber can be used as a distributed vibration sensor to perceive the external disturbance along the fiber through the phase variation of the Rayleigh backscatter light. However, due to the inevitable interference fading phenomenon, the signal-to-noise ratio (SNR) of Rayleigh backscatter light at certain points is insufficient, thus affecting the fidelity of vibration sensing. In this paper, we propose the spectrum extraction and the rotated-vector-sum (SERVS) method to suppress the interference fading in the pulse-intensity-coding Φ-OTDR, which applies Golay complementary sequence through acousto-optic modulator (AOM). Benefited from the easier implementation, the experimental results demonstrate that the percentage of fading points can be reduced from 2.98% to 0.33% significantly and the standard deviation of differential phase is also decreased from 0.6556 rad to 0.2901 rad. Also the minimum level of averaged power spectral density (PSD) of the differential phase at whole locations along the fiber is reduced about 6 dB/Hz effectively. For the demodulated disturbance signal, no influence on the SNR is observed thus it maintains a SNR improvement of 8.6 dB compared to the traditional single pulse Φ-OTDR system, achieving a noise floor of 2.38 pϵ/√Hz. [ABSTRACT FROM AUTHOR]

An essentialtask of the electronic support measures system is to deinterleave the intercepted radar pulse stream. To improve the radars' antijamming capability and adapt the radars to different application scenarios, the pulse signals emitted by various radars are becoming abundant, causing the pulse stream intercepted by the reconnaissancereceiver to becomemore and more complicated. Apart from fixed pulse repetition interval (PRI) signals, other PRI modulated signals, such as jitter PRI and staggered PRI, also appear in the intercepted radar pulse stream. The aforementioned pulse stream is defined as mixed radar signals in this article. The deinterleaving of mixed radar signals is an inevitable challenge in the field of electronic countermeasures. A novel algorithm for deinterleaving mixed radar signals is proposed in this article. It is flexible for deinterleaving different PRI modulated signals. A sequence retrieval method based on clustering ideas is also proposed in the algorithm, which enables different pulse sequences to be accurately separated. Simulation results show that the new algorithm has great PRI estimation accuracy for mixed radar signals in a large pulse missing rate. [ABSTRACT FROM AUTHOR]

Multiple-input-multiple-output synthetic aperture radar (MIMO-SAR) technology is an effective scheme to achieve there-dimensional (3-D) imaging in millimeter wave and terahertz band. Compared with the 2-D array, the system complexity and the number of array elements are greatly reduced. In this paper, an efficient image reconstruction algorithm in wavenumber domain based on phase shift migration (PSM) was proposed for MIMO-SAR 3-D real-time imaging application. By decomposing the range-wavenumber based on binomial approximation theory, the PSM operation can be achieved only by matrix multiplication and Fourier transform (FT) algorithm without time-consuming wavenumber accumulation. Proof-of-principle experiments were also carried out in 0.1THz band based on a MIMO-SAR prototype system. Both simulation and experimental results of different targets show that the image quality of the proposed algorithm is comparable to that of back-projection algorithm (BPA). The partial enlarged images of the imaging results validate that compared with the range migration algorithm (RMA) the proposed algorithm can achieve higher reconstruction accuracy with comparable efficiency. [ABSTRACT FROM AUTHOR]

Inspired by the circular-aperture synthetic aperture radar (Circular-SAR) imaging regime that can provide higher azimuth image resolution, the imaging regime employing the multiple-input–multiple-output (MIMO) arc array is proposed. Moreover, no efficient imaging algorithm is now available for these MIMO arc array setups. This article proposes a modified Omega-K algorithm for near-field azimuth image reconstruction based on the geometry transformation from the single-frequency MIMO arc array to the equivalent MIMO linear array. Note that this geometry transformation relies on the calculation of the phase difference and the definition of the corresponding compensation function. Compared with the single-input–single-output (SISO) arc scan requiring more elements, simulations with good agreement were performed to validate the azimuth image reconstructions of single/multiple targets. Although the computing efficiency of the proposed algorithm for MIMO arc array is lower than that of the traditional Omega-K algorithm for the SISO arc scan, it still has an obvious advantage relative to the traditional backprojection (BP) algorithm that is always taken as the gold standard. Furthermore, three realistic imaging geometries, including the metal strips at different radii, the tilted metal plate, and the human body torso cross section, were simulated to test the fidelity of the proposed reconstruction algorithm. Proof-of-principle experiments were also carried out based on an MIMO arc array with the help of one arc scanner. Finally, both simulation and experimental results validate the effectiveness of the proposed algorithm on azimuth image reconstruction quality. [ABSTRACT FROM AUTHOR]

As a core component of the bucking coil helicopter transient electromagnetic (TEM) system, the current pulse inverter should agree two crucial aspects, high power and fast turn-OFF. In this article, based on the design and modeling of transmitting coil and bucking coil, a novel current inverter topology based on the double constant voltage clamping technology, which differs from the traditional single clamping technology is firstly proposed and analyzed. By using double clamping technology, both the current pulse's rising edge and falling edge are improved effectively. What's more, the turn-OFF time of the current inverter is adjustable, which is of great difference from the conventional clamping technology with nonadjustable turn-OFF time. The ground and field experiments are implemented to test the performance of the current inverter. The results of the ground test of the performance comparison with worldwide VTEM transmitter verify that it successfully converts the standard 28 V dc source from helicopter power to bipolar approximately trapezoid pulses with a peak current of 300 A and a much faster turn-OFF time than the VTEM transmitter. The results of field exploration further demonstrate that it achieves a high quality of primary field compensation and effectively improve the detection capability of the helicopter TEM surveying system. [ABSTRACT FROM AUTHOR]

The growing demand for building information modeling (BIM) data and ubiquitous applications make it increasingly necessary to establish a reliable way to share the models on lightweight devices. Building scenes have strong occlusion features and the building exterior plays an important role in digital devices with limited computational resources. This allows the possibility to reduce the resource consumption while roaming in outdoor scenes by culling away the interior building data. This article addresses the task of automatic annotation of BIM building exterior via voxel index analysis. We showcase the research of using industry foundation classes (IFC) and other mainstream formats as our input data and proposed an automatic algorithm for annotating the building exterior. Afterward, a practical and accurate voxel index analysis procedure is designed for frequently flawed models. The annotation can be added directly into the original data file under the same IFC standard, avoiding the complex procedure and information loss in semantics mapping between different standards. The final examinations show the robustness of our algorithm and the capability of handling large BIM building models. [ABSTRACT FROM AUTHOR]

In complex terrain, semi-airborne transient electromagnetic surveying can effectively solve the detailed exploration problems to replace ground manual operation. This method has the advantages of high efficiency, deep exploration depth, and high signal-to-noise ratio. As the core component of the system, the constant-current transmission converter determines the primary field source of the surveying system. High-accurate and stable-output electromagnetic transmission technology is the key issues of the surveying equipment development. In this paper, the converter circuit topology is designed in detail and a novel model reference adaptive proportional-integral control algorithm is put forward. The rising overshoot of current is eliminated and falling edge is linear. Finally, the 20-kW high-power transmitting instrument has been completed and used for field experiments. A large number of experimental results show that the transmitting instrument can achieve high-power constant-current emission, stable output, and good dynamic performance. And the steady-state accuracy is better than the traditional transmitter. The converter successfully improved the semi-airborne transient electromagnetic system detection capability and achieved satisfactory results in field experiments. [ABSTRACT FROM AUTHOR]

This letter presents a two-dimensional near-field synthetic spectrum imaging algorithm based on a single-frequency sparse multiple-input–multiple-output (MIMO) array. By using an especially defined backward spreading function, the proposed algorithm migrates the scattered wave field under different illuminations. A synthetic spectrum can be obtained by synthesizing the spectrums of these migration results and then interpreted to the final reconstruction. The migration processing enables the algorithm to adapt to arbitrary apertures. Meanwhile, the influences of the limited aperture, the spreading loss, and the wavefront curvature in the near field are considered and compensated. High processing speed is achieved by using a large interpixel spacing during the migration processing and by the fast Fourier transform in the frequency-wavenumber (f-w) domain. Simulations and experiments are carried out, and the results demonstrate both the high-computational efficiency and the high flexibility for arbitrary sparse MIMO array apertures. [ABSTRACT FROM AUTHOR]

The characteristics of the range cell migration (RCM) under single-input-multiple-output (SIMO) bi-static geometry are studied and an omega-K algorithm for near-field 3-D imaging based on planar SIMO or multiple-input-multiple-output (MIMO) array is proposed. The RCM and the linear part of the range offset (RO) within SIMO data are corrected by employing a 3-D Stolt transformation. The residual range error is further compensated by phase multiplication and an image-domain interpolation. Reconstruction for a MIMO aperture can be achieved by adding together all the focusing results from its SIMO subarrays. The implementation details of the algorithm are described. The imaging resolution and the sampling requirements for a MIMO aperture are discussed. Since the RO correction is achieved by an approximate way, the spatial limitation for accurate reconstruction is also given. The imaging accuracy and the high efficiency of the algorithm are demonstrated both by simulations and experiments with various distributed targets based on planar MIMO arrays. Real-time 3-D imaging for planar SIMO/MIMO aperture is expected to be achieved by using the algorithm. [ABSTRACT FROM AUTHOR]

In order to determine a great capacity of ice thickness assessments in a short time on-site, we have designed a real-time processor by using the modern commercial DSP chip named TMS320C6678. It is essential to develop an appropriate real-time imaging algorithm adapted to this real-time processor. In this paper, we propose a novel real-time imaging algorithm named the range-Doppler algorithm (RDA) integrated with the shift-and-correlate (SAC) algorithm. The proposed method extends the standard RDA to be appropriate for numerous media while adding the SAC algorithm to realize azimuth FM rate estimation to obtain accurate echograms of interior reflecting horizons (IRHs) and bedrock of the ice sheets at different depths. Initially, theoretical study is performed to the introduced method. Next, the hardware architecture of the designed real-time embedded system is presented, as well as the implementation of the proposed method on this processor. As a final point, the method is applied to the replication point targets and high-resolution ice-sounding radar information in order to verify its correctness of ice layers picturing. Through the presented echograms of ice sheets and the comparisons with both preceding methods in both main features, we can establish that the designed real-time processor accompany with the proposed RDA integrated with the SAC algorithm is quite reliable to generate the high-resolution ice-sounding images deprived of lowering the capability to reduce the azimuth clutter. [ABSTRACT FROM AUTHOR]

A dc arc fault can be a serious threat to the safe operation of a low-voltage dc system. Typically, a fair amount of electromagnetic radiation (EMR) accompanies the arcing process. To investigate the characteristics of EMR of the series dc arc fault, a fourth-order Hilbert fractal antenna is used to detect the EMR signals generated by the dc arc. The factors influencing the characteristics of EMR including electrode material, diameter, current, and pressure are considered. The amplitudes of the EMR pulses at the arc initiation moment are measured, and fast Fourier transform is used to analyze the characteristics of the frequency spectrums. The test results indicate that the amplitudes of the EMR pulses generated by stainless steel electrodes are higher than those generated by brass, copper, and aluminum electrodes. Furthermore, the trends of the amplitudes of the EMR pulses with increasing current are different for electrodes with different diameters. Finally, it is observed that the influence of the pressure is different for different electrode materials. The characteristic frequency band of the EMR pulses of the dc arcs generated under various test conditions is in a certain range (36–41 MHz), which can be used as a detecting characteristic parameter for the series dc arc. [ABSTRACT FROM AUTHOR]